Predictive model for persistent hypertension after surgical intervention of primary aldosteronism

Primary aldosteronism (PA) is one of the most common causes of secondary hypertension and is potentially curable. However, a large number of patients still undergo persistent hypertension (PHT) after unilateral adrenal surgery. This research retrospectively studied the factors associated with this clinical difficulty and established a prediction model for the postoperative PHT; Methods: 353 patients from 2014 to 2021 with PA undergoing unilateral adrenal surgery were enrolled in this study. Clinical and biochemical characteristics were reviewed and the associating factors were examined using univariate and multivariate analysis. A nomogram-based prediction model was established correspondingly; results: 46.2% (163/190) of patients had post-surgical PHT. Multivariate analysis suggested that BMI ≥ 25, diabetes, duration of hypertension, male gender, and ARR were independent predictors of PHT after surgery. The prediction model based on the nomogram showed good discrimination ability (the C index of the training group and the validation group were 0.783 and 0.769, respectively), and the calibration curves and the Hosmer–Lemeshow test were good as well. Clinical usefulness was quantified using the decision curve analysis; This nomogram is an integration of the clinical and biochemical data of patients before surgery, and is a reliable tool with high accuracy for predicting the postoperative PHT in patients with PA.

www.nature.com/scientificreports/ must use at least one confirmatory test (captopril challenge test, saline infusion test, fludrocortisone suppression test) 2 . Patients with confirmed PA underwent computed tomography (CT) and adrenal venous samples (AVS) to locate the corresponding lesions. When patients presented with bilateral normal adrenal glands or bilateral adrenal lesions on CT, the final surgical side was determined based on the lateralization in AVS. Besides, part of patients with typical adenomas diagnosed by CT underwent surgical treatment directly without undergoing AVS. In our study, AVS was performed in 235 patients, while CT was conducted in another 118 patients. Among the patients diagnosed by CT, 43 patients were young (below 35 years old), and an additional 75 patients were pathological diagnosed typical adenomas. We excluded patients who did not achieve biochemical success to minimize the potential errors associated with using CT alone for diagnosis. Thus all the patients were diagnosed with unilateral PA. (Supplementary materials).
Definition of HHD, diabetes, RH and eGFR. The hypertensive heart disease (HHD) is diagnosed with the history of hypertension and the heart dysfunction showed in cardiac color Doppler ultrasound examination. According to the 2015 American Diabetes Association, diabetes mellitus is defined as fasting blood glucose greater than 7.0 mmol/L or blood glucose greater than 11.1 mmol/L two hours after the OGTT experiment 11 . Resistant hypertension (RH) is defined as the inability to reduce blood pressure (BP) to the normal range with at least three or more antihypertensive drugs (including diuretics) 12 . Estimated glomerular filtration rate (eGFR) was used to evaluate the renal function, which was calculated by the Modification of Diet in Renal Disease (MDRD) formula combined with age, gender, and serum creatinine 13 . Due to the incomplete information of markers such as microalbuminuria and cystatin C in partial patients, these variables were not utilized in our study.
Surgical procedure. Statistical analysis. Date distributions were analyzed by Kolmogorov-Smirnov test. Normally distributed variables were expressed as mean ± SD and were analyzed by the student t test. Otherwise, it was expressed as median (quartile range), and Mann-Whitney U test was used for it. Logarithmic transformation was used for skewed distribution data to make it normal. Chi-square test or Fisher's exact test was used to compare categorical variables. On the basis of univariate logistic regression, multicollinearity diagnostic method was carried out to eliminate variables with common causes and obvious intermediary variables. In R software, the sample.split function in the caTools of R package was used to divide the data set. All patients were divided into the training set (70%) or the validation set (30%). A nomogram predicting post-surgical PHT was established based on the results of univariate and multivariate analyses. Receiver operating characteristic (ROC) curve, concordance index (C-index), calibration plot and Hosmer-Lemeshow test were used to measure the predictive ability of the nomogram. In order to evaluate the clinical usefulness of the nomogram, decision curve analysis (DCA) was used to calculate the net benefits at different threshold probabilities. SPSS 26.0 was used in all analyses, and graphs were generated using R software. In these analyses, P < 0.05 was considered statically significant different.
Ethics approval and consent to participate. The studies involving human participants were reviewed and approved by Ethics Committee of the First Affiliated Hospital of Chongqing Medical University. All methods were carried out in accordance with relevant guidelines and regulations. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.  ). Based on previous studies, we retained BMI, duration, and gender as variables in our analysis, as these three factors can be easily obtained in clinical practice. The dosage of antihypertensive medications prior to surgery may not accurately reflect the patients' regular DDD during the referral process. We excluded it because of the potential risk of bias, although DDD may possess predictive value. Tumor diameter was excluded because it exhibited partial correlation with BMI, duration, and gender. Other variables were also excluded due to the similar reason. In the multivariate analysis (Table 3), five variables (BMI ≥ 25, male, diabetes, ARR, duration of hypertension) were all independent risk factors of the PHT. Finally, these five important variables were included to establish a nomogram (Fig. 2). The nomogram showed the score of each variable on each scale. The probability of postoperative PHT was determined by the total score of all variables. According to the model, the ROC curve of the training group and the validation group were drawn. The area under the curve (AUC) of the training group was 0.78 (95% CI 0.72-0.84), and the validation group was 0.77 (95% CI 0.68-0.86) (Fig. 3). The C index of the training group and the validation group were 0.783 and 0.769, respectively.

Results
The calibration plot revealed excellent agreement between the probability of PHT estimated by the nomogram and the actual status of PHT (Fig. 3). The Hosmer-Lemeshow test showed a P value of 0.946 in training group and 0.684 in validation group. These results showed that the nomogram is efficient in predicting PHT after surgery.

Table1. Preoperative clinical and biochemical characteristics of all patients (training + validation group).
SBP systolic blood pressure, DBP diastolic blood pressure, HT hypertension, HHD hypertensive heart disease, RH resistant hypertension, DDD defined daily dose, ARR aldosterone/renin ratio, PAC plasma aldosterone concentration, DRC direct renin concentration, Lowest serum K + lowest serum potassium in history, eGFR estimated glomerular filtration, TC total cholesterol, TG triglyceride.  www.nature.com/scientificreports/ DCA was performed in the validation group, and the results showed that when the threshold probability was about 10% to 80%, the nomogram produced a greater net benefit than a treat-all or treat-none strategy, indicating that the nomogram had good clinical value (Fig. 4).
In addition, we further compared the predictive performance of our model with ARS by ROC. The AUC value of ARS in the training group was 0.74 (95% CI 0.68-0.80), and in the validation group was 0.68 (95% CI 0.58-0.78), both lower than our predictive model (Fig. 5).

Discussion
Our study found that BMI ≥ 25, male gender, history of diabetes mellitus, ARR, and duration of hypertension were reliable predictors for the PHT postoperatively, and all the variables were easily obtainable. The nomogram based clinical prediction model was useful to predict the PHT postoperatively in patients and identify high-risk patients in order to develop a postoperative follow-up plan. Reported proportions of patients achieving clinical success vary widely between studies (20-66%) [6][7][8][9][10] . The results of our study suggested that 190 patients (53.8%) www.nature.com/scientificreports/ achieved complete clinical success through surgical treatment, and 163 patients (46.2%) had PHT, which was consistent with previous research reports. Efforts have been made to establish a predictive model in complete clinical success among PA patients [14][15][16][17][18][19] . However, the majority of prediction models are focused on predicting clinical success, and those for PHT are lacking. Besides, the prediction indicators for the two outcomes (with or without hypertension) are not entirely , it is defined as positive, and intervention (taking antihypertensive medications) may be taken. Therefore, there are benefits (pros) of intervention for patients with post-surgical PHT and harm (cons) of intervention for patients with normal BP after surgery. There is also the harm (cons) of missed intervention for patients with PHT. Pros minus cons is the net benefit. When Pi < Pt, there is no intervention, and the net benefit is 0 (treat-none). When Pi > Pt, all patients receive the intervention, and the net benefit is shown by the gray slanted curve (treat-all). Our DCA indicates that when the threshold probability is approximately 10% to 80%, the use of this predictive model would accrue greater benefit than a treat-all or treat-none strategy. www.nature.com/scientificreports/ identical. For example, previous models have paid less attention to the predictive value of diabetes mellitus absence in relation to postoperative hypertension cure. ARS and PASO score both had a high accuracy in predicting the likelihood of hypertension remission after surgery. ARS score failed to contain several recently reported predictors of surgical outcome, such as ARR 17 . In addition, the AUC of ARS is lower than that of our model, indicating that our predictive model possesses superior predictive ability. In terms of PASO score, although it included target organ damage into their model, not all patients in hypertension centers underwent echocardiography or microalbuminuria measurements, which may limit its clinical applicability 18 . Nevertheless, we have established a high accurate prediction model of PHT after surgery, and all the variables are easily obtained preoperatively. Long-lasting excessive aldosterone in plasma of PA patients can lead to vascular remodeling, ventricular hypertrophy, and myocardial damage [20][21][22][23] . Vascular remodeling may lead to the persistence of hypertension, even if the plasma aldosterone level is normalized by surgery, and the outcome cannot be reversed 24 . We found that the duration of hypertension was an independent risk factor for PHT, and it obtained the highest score in the nomogram. Therefore, early diagnosis and treatment of PA is critical to maximize the benefits of surgery.
Previous studies have shown that higher ARR is related to hypertension remission, but this association was rare shown in multivariate analysis 15 . Our study found that lower preoperative ARR was closely associated with postoperative PHT and was a reliable predictor of postoperative hypertension. Patients with lower preoperative serum potassium and higher ARR are more likely to obtain better clinical outcomes. We speculate that it may be related to the early appearance of clinical symptoms.
PA is closely related to metabolic syndrome [25][26][27] . Excessive aldosterone or concomitant hypokalemia increases the risk of diabetes. High aldosterone concentration causes impairment of pancreatic islets β cell function and decreases in sensitivity of target organs to insulin [28][29][30] . In addition, some studies suggested that PA and glucose metabolism may influence with each other 31 . Diabetes complicating PA can increase the progression of cardiovascular events and renal complications 32 . We found that high BMI (≥ 25) and history of diabetes both are independent predictors of the persistence of postoperative hypertension. Previous studies have suggested a potential association between the absence of diabetes and postoperative hypertension resolution 16,33 . Some publications pointed that there is a close association between diabetes mellitus and primary hypertension due to some shared risk factors 32,[34][35][36] . We speculated that patients with the history of diabetes mellitus were more likely to experience postoperative hypertension, possibly due to the vascular changes caused by diabetes. Additional studies should be performed to determine whether diabetes mellitus is a factor that is specific to Asian people or has wider applicability.
Our study aims at identifying patients with PHT, instead of identifying those with postoperative hypertension remission as most models do. This is because these very population (PHT) constitute the majority of the study target (the rate of PHT is 43.2% in this study), but a useful model is lacking. In conclusion, we first established a prediction model for the postoperative PHT. Clinicians could use this nomogram to predict PHT based on clinical and biochemical characteristics, and to strengthen follow-up for high-risk population. Because our present study was a single-center retrospective study, selection deviation is inevitable. In addition, the lack of external validation is a limitation, and relevant prospective multi-center clinical studies should be performed in the future to evaluate the accuracy of the proposed model.

Data availability
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